Jerry H. Ratcliffe

The Hotspot Matrix: A Framework for the Spatio-Temporal Targeting of Crime Reduction

The growth of intelligence‐led policing has placed even greater emphasis on the clear identification of crime hotspots as well as the choice of the crime reduction or detection strategy identified to combat a problem. Crime hotspots are becoming central to policing strategy in many locations, as they enable an operational commander to focus resources into the areas of highest need. This paper outlines the techniques used to identify the spatial and temporal components of crime hotspots, and utilizes these methods to identify three broad categories of temporal hotspot and three broad categories of spatial hotspot. These categories are described in the form of a Hotspot Matrix. Real examples show how the spatial and temporal characteristics combine within the hotspot matrix, and the paper concludes by showing how operational commanders and crime prevention practitioners might employ the hotspot matrix to determine an appropriate prevention or detection strategy.

Hotbeds of crime and the search for spatial accuracy

Abstract. One of the most important aspects of spatial crime analysis is the identification of hotspots: areas of the highest crime concentration. This paper advances a methodology for hotspot detection based on a global moving window approach combined with the use of local statistics to define the hotspot limit. This technique generates hotspots that both follow the urban morphology of the crime distribution and ensures their spatial segregation. The hypothesis that police officers can construct an accurate perception of crime distribution from exposure to daily policing practices is used to demonstrate an application in the use of hotspot analysis. Significant regions generated from recorded crime data are compared with perceived local hotspots catalogued from surveys with police officers. Results from this study show two discrete types of hotspot, here termed hotpoints and hotbeds. The morphology of these crime hotpoints and hotbeds is discussed and possible causes documented.

On the accuracy of TIGER-type geocoded address data in relation to cadastral and census areal units

In many applications of Geographical Information Systems (GIS) a common task is the conversion of addresses into grid coordinates. In many countries this is usually accomplished using address range TIGER-type files in conjunction with geocoding packages within a GIS. Improvements in GIS functionality and the storage capacity of large databases mean that the spatial investigation of data at the individual address level is now commonly performed. This process relies on the accuracy of the geocoding mechanism and this paper examines this accuracy in relation to cadastral records and census tracts. Results from a study of over 20 000 addresses in Sydney, Australia, using a TIGER-type geocoding process suggest that 5-7.5% (depending on geocoding method) of addresses may be misallocated to census tracts, and more than 50% may be given coordinates within the land parcel of a different property.

Aoristic Signatures and the Spatio-Temporal Analysis of High Volume Crime Patterns

The spatial analysis of crime and the current focus on hotspots has pushed the area of crime mapping to the fore, especially in regard to high volume offenses such as vehicle theft and burglary. Hotspots also have a temporal component, yet police recorded crime databases rarely record the actual time of offense as this is seldom known. Police crime data tends, more often than not, to reflect the routine activities of the victims rather than the offense patterns of the offenders. This paper demonstrates a technique that uses police START and END crime times to generate a crime occurrence probability at any given time that can be mapped or visualized graphically. A study in the eastern suburbs of Sydney, Australia, demonstrates that crime hotspots with a geographical proximity can have distinctly different temporal patterns.

A Temporal Constraint Theory to Explain Opportunity-Based Spatial Offending Patterns:

This article will examine the evidence supporting the notion that a proportion of offending is driven by the availability of opportunities presented in the routine activities of offenders’ lives. It then proceeds to summarize Miller’s time measurement theory in order to describe a basic language with which to discuss the movement of people through time and space. Armed with a notation for space-time interactions, the article explores the criminological implications of temporal constraints as a mechanism to explain a number of key concepts from environmental criminology. It is hypothesized here that the temporal constraints of daily life are the main cause of unfamiliarity with areas beyond the offender’s immediate least-distance path. As a result, temporal constraints, in conjunction with the locations of offender nodes, are a major determinant in spatio-temporal patterns of property crime.

A Micro-Spatial Analysis of the Demographic and Criminogenic Environment of Drug Markets in Philadelphia

Abstract Few studies have combined factors related to social disorganisation and factors related to opportunity theory at the microspatial level, with most studies aggregating to the block group or census tract. This study disaggregates block group census data in and around the vicinity of locations believed to encourage outdoor drug markets in Philadelphia, Pennsylvania, USA. A location quotient analysis finds that drug arrests cluster within a block or two of many suspected crime generators/attractors. Results from a zero-inflated Poisson model suggest some land use variables and factors associated with social disorganisation can help predict the location and size of drug markets; however, at the city level only retail alcohol outlets remained significant when combined with the social disorganisation-related variables, as a predictor of drug markets. The article discusses a number of potential reasons for these findings.

Crime Mapping and the Training Needs of Law Enforcement

This paper explores some of the more recent developments within crime mapping and the broader application of geographical information technology within law enforcement. The information technology (IT) revolution and the reduction in computing costs since the 1980s has brought a range of analytical tools within the budgets of most police services, and one of the most significant changes has been in the way that spatial data are handled. Law enforcement has strong geographic currents at all levels of the organisation, and this paper examines three applications of geographical information systems (GIS) within policing: hotspot mapping; CompStat; and geographic profiling. The paper concludes by discussing the future training needs using a simple model of intelligence-led crime reduction. This model suggests that training for managers to enable a greater understanding of the analyses presented to them, and how to use mapping to further crime prevention and reduction, may be as important as increasing the technical ability of crime analysts. The challenge for the immediate future of crime reduction practice in law enforcement is less to worry about the training of analysts, and more to address the inability of law enforcement management to understand and act on the crime analysis they are given.

Crime Mapping: Spatial and Temporal Challenges

Crime opportunities are neither uniformly nor randomly organized in space and time. As a result, crime mappers can unlock these spatial patterns and strive for a better theoretical understanding of the role of geography and opportunity, as well as enabling practical crime prevention solutions that are tailored to specific places. The evolution of crime mapping has heralded a new era in spatial criminology, and a re-emergence of the importance of place as one of the cornerstones essential to an understanding of crime and criminality. While early criminological inquiry in France and Britain had a spatial component, much of mainstream criminology for the last century has labored to explain criminality from a dispositional perspective, trying to explain why a particular offender or group has a propensity to commit crime. This traditional perspective resulted in criminologists focusing on individuals or on communities where the community extended from the neighborhood to larger aggregations (Weisburd et al. 2004). Even when the results lacked ambiguity, the findings often lacked policy relevance. However, crime mapping has revived interest and reshaped many criminologists appreciation for the importance of local geography as a determinant of crime that may be as important as criminal motivation. Between the individual and large urban areas (such as cities and regions) lies a spatial scale where crime varies considerably and does so at a frame of reference that is often amenable to localized crime prevention techniques. For example, without the opportunity afforded by enabling environmental weaknesses, such as poorly lit streets, lack of protective surveillance, or obvious victims (such as overtly wealthy tourists or unsecured vehicles), many offenders would not be as encouraged to commit crime.

The Crime Reduction Effects of Public CCTV Cameras: A Multi‐Method Spatial Approach

Public Closed Circuit TeleVision (CCTV) initiatives have been utilized as methods of monitoring public space for over two decades. Evaluations of these efforts to reduce crime have been mixed. Furthermore, there has been a paucity of rigorous evaluations of cameras located in the USA. In this analysis, crime in the viewshed of publicly funded CCTV cameras in Philadelphia, PA, is examined using two evaluation techniques: hierarchical linear modeling and weighted displacement quotients. An analysis that incorporates controls for long‐term trends and seasonality finds that the introduction of cameras is associated with a 13% reduction in crime. The evaluation suggests that while there appears to be a general benefit to the cameras, there were as many sites that showed no benefit of camera presence as there were locations with a positive outcome on crime. The policy implications of these findings are discussed.

Aoristic analysis: the spatial interpretation of unspecific temporal events

Temporal limitations of GIS databases are never more apparent than when the time of a change to any spatial object is unknown. This paper examines an unusual type of spatiotemporal imprecision where an event occurs at a known location but at an unknown time. Aoristic analysis can provide a temporal weight and give an indication of the probability that the event occurred within a defined period. Visualisation of temporal weights can be enhanced by modifications to existing surface generation algorithms and a temporal intensity surface can be created. An example from burglaries in Central Nottingham (UK) shows that aoristic analysis can smooth irregularities arising from poor database interrogation, and provide an alternative conceptualisation of space and time that is both comprehensible and meaningful.